Phylogenomic epidemiology of Clostridium difficile

艰难梭菌的系统发育流行病学

• 批准号: 8651412
• 负责人: Seth T Walk
• 金额: $ 10.19万
• 依托单位: MONTANA STATE UNIVERSITY - BOZEMAN
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8651412
• 关键词: Adult; Antibiotic Therapy; Award; Bacteria; Bacterial Genome; Bioinformatics; Cause of Death; Clinical; Clinical Data; Clinical Research; Clostridium difficile; Colitis; Collection; Communities; Complication; Computational Biology; Country; Data; Data Analyses; Databases; Development; Diarrhea; Discrimination; Disease; Disease Outbreaks; Ensure; Epidemiologist; Epidemiology; Exhibits; Fostering; Future; Gastroenteritis; Genes; Genetic; Genetic Variation; Genome; Genome Components; Genomics; Genotype; Glean; Goals; Health; Healthcare; Hospitals; Human; Incidence; Infection; Infectious Diseases Research; Inpatients; Knowledge; Link; Mentorship; Methods; Michigan; Minisatellite Repeats; Molecular Epidemiology; Nucleotides; Operative Surgical Procedures; Outcome; Pathogenesis; Patients; Phylogenetic Analysis; Protocols documentation; Records; Reproduction spores; Research; Research Personnel; Research Training; Resistance; Ribotypes; Ribotyping; Risk; Scientist; Severities; Severity of illness; Single Nucleotide Polymorphism; System; Testing; Toxin; Training; Training Programs; Universities; Work; base; career; clinically relevant; combinatorial; design; gastrointestinal; genome sequencing; improved; microbial host; novel; pandemic disease; pathogen; prognostic; response; skills; success; tool; training project; trait

DESCRIPTION (provided by applicant): Gastroenteritis caused by the bacterium, Clostridium difficile, is a global healthcare problem and a common complication of antibiotic therapy. A subset of toxin-producing C. difficile strains has recently emerged to cause large nosocomial outbreaks and an ongoing C. difficile pandemic. One hypothesis to explain the emergence of pandemic strains is the overproduction of toxins and an increased ability to form environmentally-resistant spores. However, recent studies that include data from a larger set of representative isolates challenge this hypothesis and illustrate the need for novel genetic characterizations that improve the surveillance and molecular epidemiology of these pathogens. The work proposed here will provide genome sequences of a broad diversity of C. difficile isolates and test the hypothesis that certain genomic traits are significantly associated with the severity of human C. difficile infection (CDI). Isolates will be collected from symptomatic hospita inpatients as part of an ongoing C. difficile clinical study at the University of Michigan. A totalof 1,500 isolates will be genotyped using high-throughput fluorescent-PCR ribotyping and subtyped using multi-locus variable number tandem repeat analysis (MLVA). Based on these characterizations, 150 representative isolates spanning the genotypic diversity of isolates and clinical spectrum of CDI severity will be selected for genome sequencing. Isolates from an additional ~200 CDI cases in our collection are presently being sequenced as part of a parallel project. Sequence data for all isolates (~350) will be bioinformatically manipulated and analyzed with respect to clinical parameters from the patient record database. Results from this analysis will epidemiologically link C. difficile genetic diversity in the form of single nucleotide polymorphisms (SNPs) with CDI severity and response to therapy. SNP data will be used to develop a novel phylogenetically-based typing system for the rapid genomic characterization of C. difficile strains. SNP typing will be used to characterize the genomic diversity of a large collection of isolates (n=5,000) and assess the bacterial genome-based correlates of CDI severity. The completion of this research requires that the candidate complete a didactic training program designed to specifically master concepts and tools from the fields of bioinformatics, computational biology, and genomics. A combination of coursework, mentorship from leaders in the field, and experiential knowledge to be gained from in depth data analysis will ensure the success of the research and the future career of the candidate.

描述（由申请人提供）：由艰难梭菌引起的胃肠炎是一个全球性的医疗保健问题，也是抗生素治疗的常见并发症。最近出现了一种产生毒素的艰难梭菌菌株，导致大规模的医院内疫情和持续的艰难梭菌大流行。解释大流行菌株出现的一种假设是毒素的过量产生和形成耐环境孢子的能力增强。然而，最近的研究包括来自更多代表性分离株的数据，对这一假设提出了挑战，并说明需要新的遗传特征来改善这些病原体的监测和分子流行病学。这里提出的工作将提供广泛多样性的艰难梭菌分离株的基因组序列，并测试某些基因组特征与人类艰难梭菌感染（CDI）的严重程度显着相关的假设。作为密歇根大学正在进行的艰难梭菌临床研究的一部分，将从有症状的住院患者中收集分离株。将使用高通量荧光 PCR 核糖分型对总共 1,500 个分离株进行基因分型，并使用多位点可变数量串联重复分析 (MLVA) 进行亚型分型。基于这些特征，将选择涵盖分离株基因型多样性和 CDI 严重程度临床谱的 150 个代表性分离株进行基因组测序。我们收集的另外约 200 个 CDI 病例中的分离株目前正在作为并行项目的一部分进行测序。所有分离株（~350）的序列数据将根据患者记录数据库中的临床参数进行生物信息处理和分析。该分析的结果将从流行病学角度将单核苷酸多态性 (SNP) 形式的艰难梭菌遗传多样性与 CDI 严重程度和治疗反应联系起来。 SNP 数据将用于开发一种新型的基于系统发育的分型系统，用于艰难梭菌菌株的快速基因组表征。 SNP 分型将用于表征大量分离株 (n=5,000) 的基因组多样性，并评估基于细菌基因组的 CDI 严重程度相关性。这项研究的完成要求候选人完成一个教学培训计划，旨在专门掌握生物信息学、计算生物学和基因组学领域的概念和工具。课程作业、该领域领导者的指导以及从深入数据分析中获得的经验知识的结合将确保研究的成功和候选人未来的职业生涯。